Feature Selection for Motor Imagery EEG Classification Based on Firefly Algorithm and Learning Automata

Feature Selection for Motor Imagery EEG Classification Based on Firefly Algorithm and Learning Automata

Motor Imagery (MI) electroencephalography (EEG) is widely studied for its non-invasiveness, easy availability, portability, and high temporal resolution. As for MI EEG signal processing, the high dimensions of features represent a research challenge. It is necessary to eliminate redundant features,...

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Bibliographic Details
Main Authors: Aiming Liu, Kun Chen, Quan Liu, Qingsong Ai, Yi Xie, Anqi Chen
Format: Article
Language:English
Published: MDPI AG 2017-11-01
Series:Sensors
Subjects:
motor imagery
electroencephalography
brain–computer interface
common spatial pattern
firefly algorithm
learning automata
Online Access:https://www.mdpi.com/1424-8220/17/11/2576

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https://www.mdpi.com/1424-8220/17/11/2576

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